Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone
The tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segm...
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doaj-28da902a0ed04a14a11c582cfb9cc4722021-03-30T03:06:22ZengIEEEIEEE Access2169-35362020-01-018116691167810.1109/ACCESS.2020.29652168957490Passive Measurement Method of Tree Height and Crown Diameter Using a SmartphoneWu Xinmei0https://orcid.org/0000-0001-7983-454XXu Aijun1https://orcid.org/0000-0001-6789-6938Yang Tingting2https://orcid.org/0000-0001-5441-1188School of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaSchool of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaSchool of Information Engineering, Zhejiang Agriculture Forestry University, Hangzhou, ChinaThe tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segment the image and extract tree's contour. Furthermore, an adaptive feature coordinate system is established to help study the conversion relationship of the coordinate systems. It has been proved that for the image points with the same abscissa pixels, their ordinate pixels have a linear relationship with its actual imaging angles. A depth extraction model is built according to this principle. Then, we obtain the rotation and translation matrix and established tree height and crown diameter models according to the mapping transformation relationship of coordinates. Experimental results reveal significant correlation between calculated and truth values. The RMSE is 0.267 m (rRMS=2.482%) for tree height and 0.209 m (rRMS=5.631%) for crown diameter. The relative errors of tree heights are less than 5.76% (MRE=2.159%); for crown diameter, the relative errors are less than 9.73% (MRE=4.95%). Overall, the accuracy of this method falls within the requirements of the continuous inventory of Chinese national forest resources.https://ieeexplore.ieee.org/document/8957490/Tree heightcrown diametermonocular visionpassive Measurementdepth extraction model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wu Xinmei Xu Aijun Yang Tingting |
spellingShingle |
Wu Xinmei Xu Aijun Yang Tingting Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone IEEE Access Tree height crown diameter monocular vision passive Measurement depth extraction model |
author_facet |
Wu Xinmei Xu Aijun Yang Tingting |
author_sort |
Wu Xinmei |
title |
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone |
title_short |
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone |
title_full |
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone |
title_fullStr |
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone |
title_full_unstemmed |
Passive Measurement Method of Tree Height and Crown Diameter Using a Smartphone |
title_sort |
passive measurement method of tree height and crown diameter using a smartphone |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
The tree height and crown diameter are important measurement attributes in forest resource survey and management. Hence, we propose a passive measurement method of tree height and crown diameter based on monocular camera of a smartphone. First, we use an feature-adaptive Mean-Shift algorithm to segment the image and extract tree's contour. Furthermore, an adaptive feature coordinate system is established to help study the conversion relationship of the coordinate systems. It has been proved that for the image points with the same abscissa pixels, their ordinate pixels have a linear relationship with its actual imaging angles. A depth extraction model is built according to this principle. Then, we obtain the rotation and translation matrix and established tree height and crown diameter models according to the mapping transformation relationship of coordinates. Experimental results reveal significant correlation between calculated and truth values. The RMSE is 0.267 m (rRMS=2.482%) for tree height and 0.209 m (rRMS=5.631%) for crown diameter. The relative errors of tree heights are less than 5.76% (MRE=2.159%); for crown diameter, the relative errors are less than 9.73% (MRE=4.95%). Overall, the accuracy of this method falls within the requirements of the continuous inventory of Chinese national forest resources. |
topic |
Tree height crown diameter monocular vision passive Measurement depth extraction model |
url |
https://ieeexplore.ieee.org/document/8957490/ |
work_keys_str_mv |
AT wuxinmei passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone AT xuaijun passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone AT yangtingting passivemeasurementmethodoftreeheightandcrowndiameterusingasmartphone |
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1724184061588537344 |